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On Reconnection of Broken Ridges and Binarization for Fingerprint Images

Paridhi Munshi, Suman K. Mitra

Abstract


With the increase in security threats, use of biometrics for person identification and authentication has been increased. One of the oldest and most widely used forms of biometric is, Fingerprint. Since it is mainly used in forensic science, accuracy in the fingerprint identification is highly important. Most of the fingerprint identification systems are based on minutiae matching and a critical step in correct matching of fingerprint is extracting minutiae reliably from adequate quality images. However, fingerprint quality may be degraded and corrupted due to variations in skin, pressure and impression conditions. One of these degradations is due to the presence of unwanted breaks or creases on the surface of the image. Moreover most of the feature extraction algorithms work on binary images instead of the gray scale image and results of the feature extraction depends on the quality of binary image used. Keeping these points in mind, an enhancement technique for reconnection of broken ridges and binarization are proposed in this paper. Both of these pre-processing are employed prior to minutiae extraction to obtain a more reliable estimation of minutiae locations and there by expect to get a robust matching performance.

Keywords: Fingerprint recognition, minutiae, enhancement, binarization


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References


Maio D., Maltoni D., Jain A. K., et al. Handbook of Fingerprint Recognition, 2nd Ed. Springer, 2005.

Galton F., Finger Prints, McMillan & Co., London, 1892.

Chang D.H., Fingerprint Recognition through Circular Sampling. J. Imaging Sci. Technol. 2000; 44(6): 560–564p.

Cheng J., Tian J., Fingerprint Enhancement with Dyadic Scale-Space, Pattern Recogn. Lett. 2004; 25: 1273–1284p.

Otsu Nobuyuki, A Threshold Selection Method from Gray-Level His-togram, IEEE T. Syst. Man Cy. 1979; 9(1): 62–66p.

Moayer B., Fu K., A Tree System Approach for Fingerprint Pattern Recog-nition, IEEE T. Pattern Anal. 1986; 8(3): 376–388p.

Gonzalez C. R., Woods E. R., Digital Image Processing, 3rd Ed., Pear-son, Upper Saddle River, NJ, 2008.

Choi J.H., Lee S., Roh S., et al. Perception based Fingerprint Image Enhancement, Signal Processing and its Applications, 9th International Symposium, ISSPA. Sharjah, Feb 2007, 1–4p.

Greenberg S., Aladjem M., Kogan D., Fingerprint Image Enhancement using Filtering Techniques. Real Time Imaging 2002; 8: 227–236p.

Henry E., Classification and Uses of Fingerprints. Rutledge, London, 1900.

Hong L., Wan Y., Jain A., Fingerprint Image Enhancement: Algorithm and Performance Evaluation. IEEE T. Pattern Anal. 1998; 20(8): 777–789p.

Komarinski P., Higgins P. T., Higgins K. M., et al. Automated Fingerprint Identification Systems, Elsevier Academic Press, 2005.

Maio D., Maltoni D., Direct Gray-scale Minutiae Detection in Fingerprints, IEEE T. Pattern Anal. 1997; 19(1): 27–40p.


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